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Regular version of the site

Information Systems

2022/2023
Academic Year
ENG
Instruction in English
5
ECTS credits
Course type:
Compulsory course
When:
2 year, 2, 3 module

Instructors


Нездоймышапко Людмила Андреевна

Course Syllabus

Abstract

The course covers theoretical and practical basics of working with quantitative data in the social sciences. We will start with the foundations of interacting with Excel, namely spreadsheet structure and basic formulas. During more advanced sessions we will study logic functions, pivot tables, and text data. A significant part of the course will be devoted to the programming language R. We will study different types and classes of objects within R as well as math and logical operators. Data subsetting in base R will be complemented by data manipulation and aggregation with tidyverse. The course will also introduce students to data visualisation with ggplot2 and tidyverse packages. Our last meetings will focus on a brief overview of several advanced R packages.
Learning Objectives

Learning Objectives

  • Explain the place of a person in the Information System
  • Introduce students to the data analysis tools such as Excel and R
  • Understand how the concept of Information Systems can be applied to social sciences
Expected Learning Outcomes

Expected Learning Outcomes

  • Able to run basic functions in Excel
  • Able to use Latex for making a presentation or short report
  • Know basic principles of programming in the framework of working with R
Course Contents

Course Contents

  • Introduction to Information Systems:
  • Introduction to Excel and Word / Latex:
  • Advanced analysis in Excel:
  • Introduction to R & Rstudio:
  • Data manipulation using Rstudio:
Assessment Elements

Assessment Elements

  • non-blocking Seminar Preparation and Activity
  • non-blocking Weekly homeworks
  • non-blocking Excel + Word / Latex (Midterm 1)
    First homework consists of two tasks. Via the first one, students are supposed to demonstrate basic skills of manipulating data and answering research questions (10 questions) with the help of Microsoft Excel. Second one is oriented on creation of basic reports in Microsoft Word / Latex.
  • non-blocking Data aggregation and visualization in R (Midterm 3)
  • non-blocking Basics of R (Midterm 2)
  • non-blocking Report based on given data
Interim Assessment

Interim Assessment

  • 2021/2022 2nd module
    0.2 * Data aggregation and visualization in R (Midterm 3) + 0.1 * Excel + Word / Latex (Midterm 1) + 0.15 * Weekly homeworks + 0.15 * Basics of R (Midterm 2) + 0.15 * Seminar Preparation and Activity + 0.25 * Report based on given data
  • 2022/2023 3rd module
  • 2023/2024 1st module
Bibliography

Bibliography

Recommended Core Bibliography

  • Field, A. V. (DE-588)128714581, (DE-627)378310763, (DE-576)186310501, aut. (2012). Discovering statistics using R Andy Field, Jeremy Miles, Zoë Field.
  • Роберт, И. R в действии. Анализ и визуализация данных в программе R : руководство / И. Роберт, Кабаков ; перевод с английского Полины А. Волковой. — Москва : ДМК Пресс, 2014. — 588 с. — ISBN 978-5-97060-077-1. — Текст : электронный // Лань : электронно-библиотечная система. — URL: https://e.lanbook.com/book/58703 (дата обращения: 00.00.0000). — Режим доступа: для авториз. пользователей.

Recommended Additional Bibliography

  • Wickham, H., & Grolemund, G. (2016). R for Data Science : Import, Tidy, Transform, Visualize, and Model Data (Vol. First edition). Sebastopol, CA: Reilly - O’Reilly Media. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1440131